[1] Dang, A., and Horn, J., Formation control of leaderfollowing uavs to track a moving target in a dynamic environment, Journal of Automation and Control Engineering, Vol. 3(1), (2015).
[2] Achmadi, S., Marjono, and Miswanto, Analysis multi-agent with precense of the leader, in AIP Conference Proceedings, AIP Publishing LLC, (2017).
[3] Consolini, L., and et al., Leader–follower formation control of nonholonomic mobile robots with input constraints, Automatica, Vol. 44(5), pp. 1343-1349, (2008).
[4] Peng, Z., and et al., Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics, IEEE Transactions on Control Systems Technology, Vol. 21(2), pp. 513-520, (2012).
[5] Qian, D., Tong, S., and Li, C., Leader‐Following Formation Control of Multiple Robots with Uncertainties through Sliding Mode and Nonlinear Disturbance Observer, Etri Journal, Vol.38(5), pp. 1008-1018, (2016).
[6] Ren, W., and Beard, R.W., Decentralized scheme for spacecraft formation flying via the virtual structure approach, Journal of Guidance, Control, and Dynamics, Vol. 27(1), pp. 73-82, (2004).
[7] Lewis, M.A., and Tan, K.-H., High precision formation control of mobile robots using virtual structures, Autonomous robots, Vol. 4(4), pp. 387- 403, (1997).
[8] Pantelimon, G., et al., Survey of Multi-agent Communication Strategies for Information Exchange and Mission Control of Drone Deployments, Journal of Intelligent & Robotic Systems, Vol. 95(3-4), pp. 779-788, (2019).
[9] Liu, Y., and Bucknall, R., A survey of formation control and motion planning of multiple unmanned vehicles, Robotica, Vol. 36(7), pp. 1019-1047, (2018).
[10] Issa, B., and A.T., Rashid, A survey of Multi-Mobile Robots Formation Control, International Journal of Computer Applications, Vol. 181(48), pp. 12-16, (2019).
[11] Ai, X.L., and et al., Optimal formation control with limited communication for multi-unmanned aerial vehicle in an obstacle-laden environment, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 231(6), pp. 979-997, (2017).
[12] Do, K.D., and Pan, J., Nonlinear formation control of unicycle-type mobile robots, Robotics and Autonomous Systems, Vol. 55(3), pp. 191-204,
(2007).
[13] Lee, G., and Chwa, D., Decentralized behaviorbased formation control of multiple robots considering obstacle avoidance, Intelligent Service Robotics, Vol. 1(11), pp. 127-138, (2018).
[14] Alasty A., Etemadi, E.S., and Roshan-Ghalb F., Behavioral Control of Autonomous Swarms, in 16th. Annual (International) Conference on Mechanical Engineering-ISME 2008, Shahid Bahonar University of Kerman: Iran, (2008).
[15] Balch, T., and Arkin, R.C., Behavior-based formation control for multirobot teams, IEEE transactions on robotics and automation, Vol. 14(6), pp. 926-939, (1998).
[16] Khatib, O., Real-time obstacle avoidance for manipulators and mobile robots, in Autonomous robot vehicles, Springer, pp. 396-404, (1986).
[17] Dang, A.-D., and et al., Distributed formation control for autonomous robots in dynamic environments. arXiv preprint arXiv:1705.02017, (2017).
[18] Keymasi Khalaji, A., and Tourajizadeh, H., Nonlinear Lyapounov based control of an underwater vehicle in presence of uncertainties and obstacles, Ocean Engineering, Vol. 198, pp. 106998, (2020).
[19] Keymasi Khalaji, A., and saadat, I., Tracking control of quadrotors in the presence of obstacles based on potential field method, Amirkabir Journal of Mechanical Engineering, Vol. 53 (Issue 2 (Special Issue)), pp. 1095-1110, (2021).
[20] Shibahara, S., Wakasa, T., and Sawada, K., Network weight and time-varying potential function for obstacle avoidance of swarm robots in column formation, SICE Journal of Control, Measurement, and System Integration, Vol. 15(1), pp. 24-35, (2022).
[21] Harder, S.A., and Lauderbaugh, L.K., Formation specification for control of active agents using artificial potential fields, Journal of Intelligent and Robotic Systems, Vol. 95(2), pp. 279-290, (2019).
[22] Gazi, V., and et al., Aggregation, foraging, and formation control of swarms with non-holonomic agents using potential functions and sliding mode techniques, Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 15(2), pp. 149-168, (2007).
[23] Yao, J., Ordonez, R., and Gazi, V., Swarm tracking using artificial potentials and sliding mode control, (2007).
[24] Gazi, V., and et al., A target tracking approach for nonholonomic agents based on artificial potentials and sliding mode control, Asme, (2012).
[25] Olfati-Saber, R., Flocking for multi-agent dynamic systems: Algorithms and theory, IEEE Transactions on automatic control, Vol. 51(3), pp. 401-420, (2006).
[26] Utkin, V., and et al., Conventional and high order sliding mode control, Journal of the Franklin Institute, Vol. 357(15), pp. 10244-10261, (2020).
[27 Hu, J., and et al., A survey on sliding mode control for networked control systems, International Journal of Systems Science, Vol. 52(6), pp. 1129-1147, (2021).
[29] Gazi, V., and Passino, K.M., Swarm stability and optimization, Springer Science and Business Media, (2011).